library(dplyr)
library(magrittr)
load(params$RData_image)
plot_precentage_of_samples_over_min_abd
**Figure 1:** Percentage of coverage

Figure 1: Percentage of coverage

plot_precentage_of_samples_over_min_abd_byRun
**Figure 2:** Percentage of coverage per Run

Figure 2: Percentage of coverage per Run

plot_precentage_of_samples_over_min_abd_byVariable1
**Figure 3:** Percentage of coverage per catagories in Variable1

Figure 3: Percentage of coverage per catagories in Variable1

print(paste0(length(n_off_target_alleles), ' allele(s) match(es) the criteria to define off-target products'))
## [1] "0 allele(s) match(es) the criteria to define off-target products"
print(paste0(length(n_flanking_INDEL_alleles), ' allele(s) match(es) the criteria to identify products with flanking INDELs'))
## [1] "0 allele(s) match(es) the criteria to identify products with flanking INDELs"
print(paste0(length(n_PCR_errors_alleles), ' allele(s) match(es) the criteria to identify PCR_errors'))
## [1] "12 allele(s) match(es) the criteria to identify PCR_errors"
if(length(n_off_target_alleles) > 0){
  plot_off_target_stats
}
if(length(n_off_target_alleles) > 0){
  off_target_stats%>%
  DT::datatable(extensions = 'Buttons',
                options = list(dom = 'Blfrtip',
                  buttons = c('csv', 'excel')))
}
if(length(n_flanking_INDEL_alleles) > 0){
  plot_flanking_INDEL_stats
}
if(length(n_flanking_INDEL_alleles) > 0){
  flanking_INDEL_stats%>%
  DT::datatable(extensions = 'Buttons',
                options = list(dom = 'Blfrtip',
                  buttons = c('csv', 'excel')))
}
if(length(n_PCR_errors_alleles) > 0){
  plot_PCR_errors_stats
}
**Figure 5:** Flanking INDELs

Figure 5: Flanking INDELs

if(length(n_PCR_errors_alleles) > 0){
  PCR_errors_stats%>%
  DT::datatable(extensions = 'Buttons',
                options = list(dom = 'Blfrtip',
                  buttons = c('csv', 'excel')))
}
ReadDepth_coverage$plot_read_depth_heatmap
**Figure 5:** Read Coverage per sample per locus

Figure 5: Read Coverage per sample per locus

ReadDepth_coverage_by_run$plot_read_depth_heatmap
**Figure 5:** Read Coverage per sample per locus by run

Figure 5: Read Coverage per sample per locus by run

ReadDepth_coverage_by_run_controls$plot_read_depth_heatmap
**Figure 5:** Read Coverage of controls per locus by run

Figure 5: Read Coverage of controls per locus by run

all_loci_amplification_rate
**Figure 5:** Locus amplification rate distribution

Figure 5: Locus amplification rate distribution

samples_amplification_rate
**Figure 5:** Sample amplification rate distribution

Figure 5: Sample amplification rate distribution

Cigar table without masking and filter

cigar_table_unmasked_unfiltered %>%
  DT::datatable(extensions = 'Buttons',
                options = list(dom = 'Blfrtip',
                  buttons = c('csv', 'excel')))

Masked and filtered cigar table without controls

cigar_table_masked_filtered %>%
  DT::datatable(extensions = 'Buttons',
                options = list(dom = 'Blfrtip',
                  buttons = c('csv', 'excel')))

Masked and filtered cigar table of controls

cigar_table_controls_masked_filtered %>%
  DT::datatable(extensions = 'Buttons',
                options = list(
                  buttons = c('csv', 'excel')))